Senior AI Systems Integration Specialist

2 weeks ago

Nagpur, Maharashtra, India beBeeDevelopment Full time US$ 1,50,000 - US$ 2,00,000

Empowering Organizations with Intelligence and Integrity

At the forefront of enterprise analytics, we're redefining the future by harnessing the power of symbolic AI, vector, and graph AI. Our mission is to empower organizations with unparalleled intelligence while upholding the highest standards of integrity and societal impact.

The Opportunity

We're seeking a passionate and sharp Full Stack Developer to architect and build front-end and back-end systems for our platform. You'll work closely with our AI Engineers to create a scalable, intuitive platform that visualizes complex network relationships, delivers real-time risk scores, and integrates with advanced AI models.

This is a chance to solve intricate technical challenges, from real-time very large data processing to interactive graph visualizations, while contributing to a mission that fights financial crime, builds customer intelligence and promotes ethical decision-making.

Key Responsibilities:

  • Frontend & Visualization (40%): Build responsive, scalable web apps for advanced enterprise analytics and data visualization, develop interactive graph/network visualizations capable of rendering millions of nodes and edges smoothly, optimize frontend performance for real-time exploration of large, multi-dimensional datasets, design interfaces for explainable AI and complex entity relationship analytics, implement advanced rendering techniques (WebGL, canvas virtualization) for massive dataset visualization.
  • Backend & API Development (35%): Architect and implement fast, scalable GraphQL/REST APIs with sub-sec response times for analytics, entity resolution, and graph queries, develop and orchestrate microservices using Node.js, Python, Scala, build and maintain data transformation and aggregation pipelines, optimizing for low-latency and high throughput, integrate backend analytics powered by Apache Hadoop, Spark, and our proprietary graph database, work with our custom graph query language and SDKs to expose graph analytics capabilities.
  • Cloud Infrastructure & Data Platform (25%): Deploy, scale, and monitor services on GCP (Kubernetes, GKE, Cloud Run, Pub/Sub), implement cloud functions and serverless analytics workflows, design and optimize large-scale data processing pipelines handling TB-scale data with Apache Hadoop and Spark, collaborate with data engineers on ETL processes, data architecture, and real-time data integration strategies, ensure platform reliability with 99.9% uptime SLAs.
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